A group of individuals selling AI services on a second-hand trading platform has reportedly achieved impressive financial success within just six months. While tech giants like Alibaba, ByteDance, and Baidu make headlines with their billion-dollar investments in AI, the real-world monetisation of this technology is quietly happening in an unexpected place.
Data from the platform shows that in the first half of this year, AI service orders reached 9.816 million, a 157% increase year-on-year. This surge brought nearly five million buyers to the platform for AI-related services. On average, this translates to about 50,000 to 60,000 AI transactions happening daily. Among these, AI programming orders skyrocketed by over 1700%, AI animated series saw a 1400% increase, and even services like AI-assisted PPT creation rose by 260%.
The question arises: why is this technology, developed with massive investment from tech conglomerates, finding its most scalable and accessible commercial application on a second-hand trading site?
To understand this phenomenon, it is helpful to look at who is selling and buying these services. The seller demographic is dominated by young individuals, with over 60% of sellers aged between 18 and 35. Interestingly, female sellers account for a significant 62.4% of the total, challenging the typical stereotype of an AI professional. While one might expect programmers or engineers to lead this trend, the data suggests that everyday people are actually capitalizing on this opportunity. This success is built on a foundation of skills that were already being offered on the platform, with AI just being the fastest-growing new category.
From a product perspective, the offerings are diverse. Sellers provide everything from AI painting, design, animation, video, and voice-over services to AI virtual portraits and programming. The services also range in complexity from custom workflow and intelligent agent setup to content creation. The market is structured in layers, with AI skills and gig-based orders being the most common at 45.1% of all transactions, followed by tutorials and courses at 8.1%, and templates and workflows at 6.6%.
While the average monthly turnover for sellers is a modest 897 yuan, primarily serving as a side hustle, some have reached a much larger scale. For instance, one successful seller managed to move 17,000 units of an AI animation tutorial in just six months. Even at a low unit price, this translates to a six-figure income. On the other end of the spectrum, technical deployment services, while fewer in number, command significantly higher per-order values, sometimes in the tens of thousands of yuan, creating substantial returns for those serving business clients.
The buyers are predominantly regular users, including students, professionals, and content creators. Their needs range from polishing presentation materials for thesis defenses to purchasing image and video creation services. Small businesses also seek cost-effective solutions for website building and AI application development. Despite the availability of free AI tools, there is a clear commercial gap, as many users lack the expertise to choose the right tool or articulate their needs effectively, making them willing to pay for convenience.
So why has this platform become the go-to place for such services? The core reason lies in a massive, previously unaddressed gap in the market. Traditional software companies focus on high-value projects, while professional outsourcing teams are too costly for small tasks. This leaves a vast middle ground of micro-orders that are too small for large service providers. The platform effectively aggregates these scattered, microscopic demands, making it feasible to find someone to complete a 50-yuan task. This marketplace concept has proven to be highly scalable, creating economic activity that might otherwise not exist.
The consumer-to-consumer (C2C) model is a significant advantage. Sellers don't need to set up complex online storefronts; they can simply post a service description and examples to test the market. This low barrier to entry is key. Also, the negotiation-heavy nature of AI work fits naturally with the platform's existing trading culture. This model also solves a geographic problem. Sellers from smaller cities make up a large portion of the market, as these areas often lack local digital services. The platform removes geographical barriers, enabling a designer from a small town to serve clients nationwide.
The true value brought by this platform is not in its AI technology, but in its ability to connect supply and demand. Large language models have lowered the cost of production, and the platform has lowered the cost of finding customers. It is this combination that makes small, low-value requests commercially viable. AI has provided everyday people with a tool, and the platform has given them a marketplace.
However, despite its vibrancy, this business has a low ceiling. The low entry barrier leads to a rapid increase in supply. Simple tutorials and templates are easy to copy, and new sellers often resort to price wars to gain their first orders. This increased efficiency and supply ultimately puts downward pressure on prices across the board.
The business model also faces a scaling dilemma. While products like tutorials can be sold repeatedly with minimal effort, they are also most susceptible to copying. Conversely, custom development services can be more profitable but are limited by the seller's personal time. Achieving both high margins and large scale simultaneously is challenging. With the platform adjusting its software service fee for certain operators in April 2026, profit margins for low-cost services could be squeezed further once model costs and after-sales time are factored in.
More concerning than price wars are compliance risks. Regulatory bodies have already classified purchasing or ghostwriting academic papers as misconduct, and some sellers are circumventing platform rules by using vague descriptions for bulk-generated content. This presents a significant governance challenge. The platform needs to develop better mechanisms to verify product delivery, manage refunds, and enhance its ability to detect violations, all while setting clear standards for different types of digital services.
Despite these hurdles, the value of nearly ten million AI orders extends far beyond just being a popular category. It proves the platform's capacity to expand its core business from physical second-hand goods to encompassing personal time and skills. This opens up new avenues for monetization through service fees and management tools. If a proper governance system for digital services can be established, this segment could well become a key growth engine for the platform, separate from its traditional second-hand trading business.